• Title/Summary/Keyword: Data Set Comparing

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Supremacy of Realized Variance MIDAS Regression in Volatility Forecasting of Mutual Funds: Empirical Evidence From Malaysia

  • WAN, Cheong Kin;CHOO, Wei Chong;HO, Jen Sim;ZHANG, Yuruixian
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.7
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    • pp.1-15
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    • 2022
  • Combining the strength of both Mixed Data Sampling (MIDAS) Regression and realized variance measures, this paper seeks to investigate two objectives: (1) evaluate the post-sample performance of the proposed weekly Realized Variance-MIDAS (RVar-MIDAS) in one-week ahead volatility forecasting against the established Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model and the less explored but robust STES (Smooth Transition Exponential Smoothing) methods. (2) comparing forecast error performance between realized variance and squared residuals measures as a proxy for actual volatility. Data of seven private equity mutual fund indices (generated from 57 individual funds) from two different time periods (with and without financial crisis) are applied to 21 models. Robustness of the post-sample volatility forecasting of all models is validated by the Model Confidence Set (MCS) Procedures and revealed: (1) The weekly RVar-MIDAS model emerged as the best model, outperformed the robust DAILY-STES methods, and the weekly DAILY-GARCH models, particularly during a volatile period. (2) models with realized variance measured in estimation and as a proxy for actual volatility outperformed those using squared residual. This study contributes an empirical approach to one-week ahead volatility forecasting of mutual funds return, which is less explored in past literature on financial volatility forecasting compared to stocks volatility.

The impact of fuel depletion scheme within SCALE code on the criticality of spent fuel pool with RBMK fuel assemblies

  • Andrius Slavickas;Tadas Kaliatka;Raimondas Pabarcius;Sigitas Rimkevicius
    • Nuclear Engineering and Technology
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    • v.54 no.12
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    • pp.4731-4742
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    • 2022
  • RBMK fuel assemblies differ from other LWR FA due to a specific arrangement of the fuel rods, the low enrichment, and the used burnable absorber - erbium. Therefore, there is a challenge to adapt modeling tools, developed for other LWR types, to solve RBMK problems. A set of 10 different depletion simulation schemes were tested to estimate the impact on reactivity and spent fuel composition of possible SCALE code options for the neutron transport modelling and the use of different nuclear data libraries. The simulations were performed using cross-section libraries based on both, VII.0 and VII.1, versions of ENDF/B nuclear data, and assuming continuous energy and multigroup simulation modes, standard and user-defined Dancoff factor values, and employing deterministic and Monte Carlo methods. The criticality analysis with burn-up credit was performed for the SFP loaded with RBMK-1500 FA. Spent fuel compositions were taken from each of 10 performed depletion simulations. The criticality of SFP is found to be overestimated by up to 0.08% in simulation cases using user-defined Dancoff factors comparing the results obtained using the continuous energy library (VII.1 version of ENDF/B nuclear data). It was shown that such discrepancy is determined by the higher U-235 and Pu-239 isotopes concentrations calculated.

A Study on the Prediction of Recycled Aggregate Concrete Strength Using Case-Based Reasoning and Artificial Neural Network (사례기반 추론과 인공신경망을 적용한 순환골재콘크리트 강도 추정에 관한 비교 연구)

  • Kim Dae-Won;Choi hee-Bok;Kang Kyung-In
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2005.05a
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    • pp.119-124
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    • 2005
  • It is necessary for prediction of recycled aggregate concrete(RAC) strength at the early stage that facilitate concrete form removal and scheduling for construction. However, to predict RAC strength is difficult because of being influenced by complicated many factors. Therefore, this research suggest optimized estimation method that can reflect many factors. One way is Case-Based Reasoning(CBR) that solved new problems by adapting solutions to similar problems solved in the past, which are solved in the case library. Other way is Artificial Neural Networks(ANN) that solved new problems by training using a set of data, which is representative of problem domain. This study is to propose comparing accuracy of the estimating the compressive strength of recycled aggregate concrete using Case-Based Reasoning(CBR) and Artificial Neural Networks(ANN).

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A Study on the exactitude of simulation tool by using Illuminate formula - Focused on the comparing result of Point method and Lightscapet - (조명공식을 이용한 시뮬레이션도구의 정확성에 관한 연구 - 점조도 공식과 Lightscape 결과 비교를 중심으로 -)

  • Kim, Chul-Hoon;Lee, Jung-Wook
    • Proceedings of the Korean Institute of Interior Design Conference
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    • 2006.05a
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    • pp.240-243
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    • 2006
  • This thesis is a study on the exactitude of Simulation Tool by using illuminate formula. Lightscape looks like general 3d program, but is a lighting simulation program that set up the properties of materials and light-sources about the model. This thesis calculates illuminance by a formula and simulates a light simulation using Lightscape for two luminaires data in space of ideal environment. As then each value was compared. As a result we got an error under 1% on the whole.

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Indirect Cutting Force Estimation Using Artificial Neural Network (인공 신경망을 이용한 절삭력 간접 측정)

  • 최지현;김종원
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.1054-1058
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    • 1995
  • There have been many research works for the indirect cutting force measurement in machining process, which deal with the case of one-axis cutting process. In multi-axis cutting process, the main difficulties to estimate the cutting forces occur when the feed direction is reversed. This paper presents the indirect cutting force measurement method in contour NC milling processes by using current signals of servo motors. An artificial neural network (ANN) system are suggested. An artificial neural network(ANN) system is also implemented with a training set of experimental cutting data to measure cutting force indirectly. The input variables of the ANN system are the motor currents and the feedrates of x and y-axis servo motors, and output variable is the cutting force of each axis. A series of experimental works on the circular interpolated contour milling process with the path of a complete circle has been performed. It is concluded that by comparing the ANN system with a dynamometer measuring cutting force directil, the ANN system has a good performance.

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Calibrated Parameters with Consistency for Option Pricing in the Two-state Regime Switching Black-Scholes Model (국면전환 블랙-숄즈 모형에서 정합성을 가진 모수의 추정)

  • Han, Gyu-Sik
    • Journal of Korean Institute of Industrial Engineers
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    • v.36 no.2
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    • pp.101-107
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    • 2010
  • Among a variety of asset dynamics models in order to explain the common properties of financial underlying assets, parametric models are meaningful when their parameters are set reliably. There are two main methods from which we can obtain them. They are to use time-series data of an underlying price or the market option prices of the underlying at one time. Based on the Girsanov theorem, in the pure diffusion models, the parameters calibrated from the option prices should be partially equivalent to those from time-series underling prices. We call this phenomenon model consistency. In this paper, we verify that the two-state regime switching Black-Scholes model is superior in the sense of model consistency, comparing with two popular conventional models, the Black-Scholes model and Heston model.

Target Detection and Navigation System for a mobile Robot

  • Kim, Il-Wan;Kwon, Ho-Sang;Kim, Young-Joong;Lim, Myo-Taeg
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2337-2341
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    • 2005
  • This paper presents the target detection method using Support Vector Machines(SVMs) and the navigation system using behavior-based fuzzy controller. SVM is a machine-learning method based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate detection of target objects as a supervised-learning problem and apply SVM to detect at each location in the image whether a target object is present or not. The behavior-based fuzzy controller is implemented as an individual priority behavior: the highest level behavior is target-seeking, the middle level behavior is obstacle-avoidance, the lowest level is an emergency behavior. We have implemented and tested the proposed method in our mobile robot "Pioneer2-AT". Comparing with a neural-network based detection method, a SVM illustrate the excellence of the proposed method.

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Feasibility Study on Environment-friendly Project to Improve Habitability in National Rental Apartment - focused on Gwangju City - (국민임대주택 주거환경 개선을 위한 친환경사업의 타당성 분석 - 광주광역시를 대상으로 -)

  • Park, Hyeon-Ku;Lee, Hyun-Chul
    • Journal of the Korean housing association
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    • v.20 no.5
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    • pp.23-30
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    • 2009
  • In case of national rental apartment, habitability is generally evaluated low comparing with typical apartments. So, researches and investment are required to increase the residential environment. In this point of view, present study aims to suggest the basic data for improvement of homeless masses' dwelling level through economic feasibility analysis. Firstly national rental apartment, which habitability is considered to be low in the point of environment-friendly, welfare, and convenience, is chosen as objective. Secondly environment-friendly project items including project flow were set up, and then basic model was formed to evaluate economic feasibility through priority survey to residents. In result, priority for two items among six different proposals were higher than the others. This result could be useful when trying to increase the dwelling level of national rental apartment being planned to construct in future.

Extraction of figures and characters with the aid of color discrimination

  • Sakai, Y.;Kitazawa, M.;Kuo, Y.
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.303-306
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    • 1995
  • The present paper deals with extraction of figures and characters from their background using the knowledge of color. At each pixel of the image on the CRT sent from a video camera, RGB values are transformed into the values in another color system, HSI, where "H" denotes hue;"S" denotes saturation;"I" denotes intensity. Representing color in HSI color space is advantageous, since a human feels color mainly in hue with the aid of brightness and purity. Comparing HSI data thus obtained with the masked original image detects noise-free edges included in the orginal image. Then setting a set of HSI thresholds and changing it identifies the portion of image of the same color. This color information is used in recongnizing characters and figures as an auxiliary system of a hierachical figure categorization method for characters and figures recognition.cters and figures recognition.

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Charges of TIP4P water model for mixed quantum/classical calculations of OH stretching frequency in liquid water

  • Jeon, Kiyoung;Yang, Mino
    • Rapid Communication in Photoscience
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    • v.5 no.1
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    • pp.8-10
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    • 2016
  • The potential curves of OH bonds of liquid water are inhomogeneous because of a variety of interactions with other molecules and this leads to a wide distribution of vibrational frequency which hampers our understanding of the structure and dynamics of water molecules. Mixed quantum/classical (QM/CM) calculation methods are powerful theoretical techniques to help us analyze experimental data of various vibrational spectroscopies to study such inhomogeneous systems. In a type of those approaches, the interaction energy between OH bonds and other molecules is approximately represented by the interaction between the charges located at the appropriate interaction sites of water molecules. For this purpose, we re-calculated the values of charges by comparing the approximate interaction energies with quantum chemical interaction energies. We determined a set of charges at the TIP4P charge sites which better represents the quantum mechanical potential curve of OH bonds of liquid water.